Instructions to use hieunguyen1053/bert-ner-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hieunguyen1053/bert-ner-vi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hieunguyen1053/bert-ner-vi")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hieunguyen1053/bert-ner-vi") model = AutoModelForTokenClassification.from_pretrained("hieunguyen1053/bert-ner-vi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb4537bd6a48375171d5b6737de3b274e4cd28a13486053b651a37f67e2e9863
- Size of remote file:
- 388 MB
- SHA256:
- e700f011a42dde236c2c7e5371749e12f9d434bda9d1958a369283da04ab796a
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